Daryl Goh
成为会员时间:2020
白银联赛
9500 积分
成为会员时间:2020
这是一节入门级微课程,旨在解释什么是负责任的 AI、它的重要性,以及 Google 如何在自己的产品中实现负责任的 AI。此外,本课程还介绍了 Google 的 7 个 AI 开发原则。
本课程简要介绍了编码器-解码器架构,这是一种功能强大且常见的机器学习架构,适用于机器翻译、文本摘要和问答等 sequence-to-sequence 任务。您将了解编码器-解码器架构的主要组成部分,以及如何训练和部署这些模型。在相应的实验演示中,您将在 TensorFlow 中从头编写简单的编码器-解码器架构实现代码,以用于诗歌生成。
本课程教您如何使用深度学习来创建图片标注模型。您将了解图片标注模型的不同组成部分,例如编码器和解码器,以及如何训练和评估模型。学完本课程,您将能够自行创建图片标注模型并用来生成图片说明。
本课程向您介绍扩散模型。这类机器学习模型最近在图像生成领域展现出了巨大潜力。扩散模型的灵感来源于物理学,特别是热力学。过去几年内,扩散模型成为热门研究主题并在整个行业开始流行。Google Cloud 上许多先进的图像生成模型和工具都是以扩散模型为基础构建的。本课程向您介绍扩散模型背后的理论,以及如何在 Vertex AI 上训练和部署此类模型。
本课程向您介绍 Transformer 架构和 Bidirectional Encoder Representations from Transformers (BERT) 模型。您将了解 Transformer 架构的主要组成部分,例如自注意力机制,以及该架构如何用于构建 BERT 模型。您还将了解可以使用 BERT 的不同任务,例如文本分类、问答和自然语言推理。完成本课程估计需要大约 45 分钟。
本课程将向您介绍注意力机制,这是一种强大的技术,可令神经网络专注于输入序列的特定部分。您将了解注意力的工作原理,以及如何使用它来提高各种机器学习任务的性能,包括机器翻译、文本摘要和问题解答。
这是一节入门级微课程,旨在解释什么是生成式 AI、它的用途以及与传统机器学习方法的区别。该课程还介绍了可以帮助您开发自己的生成式 AI 应用的各种 Google 工具。
这是一节入门级微学习课程,探讨什么是大型语言模型 (LLM)、适合的应用场景以及如何使用提示调整来提升 LLM 性能,还介绍了可以帮助您开发自己的 Gen AI 应用的各种 Google 工具。
Description: According to IDC, by 2026, 7 PB of data will be generated per second globally. But what you *do* with the data is what matters. Data is the heart of digital transformation and offers incredible opportunities for organizations to accelerate the most strategic business outcomes, like revenue and productivity. Want to grow your skills and take advantage of the opportunity? Play now to get hands-on experience with Google Cloud's powerful data tools. Each lab teaches and tests your growing tech skills, and sets you on the path to your first Google Cloud credential.
完成在关联工作表中分析 BigQuery 数据这一技能徽章课程,展示您能够使用关联工作表,在 Google 表格的电子表格中访问、分析、可视化并共享数十亿行 BigQuery 数据。
Cloud Storage, Cloud Functions 和 Cloud Pub/Sub 都是 Google Cloud Platform 服务,可用于存储、处理和管理数据。这三项 服务可结合使用,创建各种数据驱动型应用。在 此技能徽章课程中,您将使用 Cloud Storage 存储图片,使用 Cloud Functions 函数 处理图片,并使用 Cloud Pub/Sub 将图片发送到另一个应用。
More than 90% of IT leaders say they're looking to grow their cloud environments in the next several years, yet more than 80% of those same leaders identified a lack of skills as a barrier to growth. This means that tech skills (particularly cloud skills!) are in high demand. Want to grow your skills and take advantage of the opportunity? Play now to get hands-on experience with Google Cloud. Each lab teaches and tests your growing tech skills, and sets you on the path to your first Google Cloud credential. No experience required.
完成监控和管理 Google Cloud 资源这一入门级技能徽章课程,展示您在以下方面的技能:授予和撤消 IAM 权限; 安装 Monitoring 代理和 Logging 代理;创建、部署和测试事件驱动型 Cloud Run 函数。
完成为 Looker 信息中心和报告准备数据入门级技能徽章课程, 展现您在以下方面的技能:对数据进行过滤、排序和透视;将来自不同 Looker 探索的结果合并; 以及使用函数和运算符构建 Looker 信息中心和报告以用于数据分析和可视化。
完成在 Google Cloud 上使用 Machine Learning API 课程,赢取高级技能徽章。 在本课程中,您将了解以下机器学习和 AI 技术的基本功能: Cloud Vision API、Cloud Translation API 和 Cloud Natural Language API。
In this quest, you will get hands-on experience with LookML in Looker. You will learn how to write LookML code to create new dimensions and measures, create derived tables and join them to Explores, filter Explores, and define caching policies in LookML.
It's no secret that machine learning is one of the fastest growing fields in tech, and Google Cloud has been instrumental in furthering its development. With a host of APIs, Google Cloud has a tool for just about any machine learning job. In this advanced-level course, you will get hands-on practice with machine learning APIs by taking labs like Detect Labels, Faces, and Landmarks in Images with the Cloud Vision API. Looking for a hands-on challenge lab to demonstrate your skills and validate your knowledge? Enroll in and finish the additional challenge lab at the end of this quest to receive an exclusive Google Cloud digital badge.
Using large scale computing power to recognize patterns and "read" images is one of the foundational technologies in AI, from self-driving cars to facial recognition. The Google Cloud Platform provides world class speed and accuracy via systems that can utilized by simply calling APIs. With these and a host of other APIs, GCP has a tool for just about any machine learning job. In this introductory quest, you will get hands-on practice with machine learning as it applies to image processing by taking labs that will enable you to label images, detect faces and landmarks, as well as extract, analyze, and translate text from within images.
众所周知,机器学习是发展最快的技术领域之一, Google Cloud Platform 在推动其发展方面发挥了重要作用。 GCP 提供了一系列 API,几乎可以满足任何机器学习作业的需求。在 本入门课程中,您将了解机器学习在语言处理方面的运用, 通过实操实验学习 如何从文本中提取实体,执行情感和语法分析,以及 使用 Speech-to-Text API 进行转写。
In this series of labs you will learn how to use BigQuery to analyze NCAA basketball data with SQL. Build a Machine Learning Model to predict the outcomes of NCAA March Madness basketball tournament games.
大数据、机器学习和人工智能是当今计算领域的热门话题, 但这些领域的专业性很强,因而很难找到 入门资料。幸运的是,Google Cloud 在这些领域提供了方便用户使用的服务, 通过本入门级课程,您可以 开始学习使用 BigQuery、Cloud Speech API 和 Video Intelligence 等工具。
Cloud SQL is a fully managed database service that stands out from its peers due to high performance, seamless integration, and impressive scalability. In this quest you will receive hands-on practice with the basics of Cloud SQL and quickly progress to advanced features, which you will apply to production frameworks and application environments. From creating instances and querying data with SQL, to building Deployment Manager scripts and connecting Cloud SQL instances with applications run on GKE containers, this quest will give you the knowledge and experience needed so you can start integrating this service right away.
Looking to build or optimize your data warehouse? Learn best practices to Extract, Transform, and Load your data into Google Cloud with BigQuery. In this series of interactive labs you will create and optimize your own data warehouse using a variety of large-scale BigQuery public datasets. BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, enroll in and finish the additional challenge lab at the end of this quest to receive an exclusive Google Cloud digital badge.
完成中级技能徽章课程使用 BigQuery 构建数据仓库,展示以下技能: 联接数据以创建新表、排查联接故障、使用并集附加数据、创建日期分区表, 以及在 BigQuery 中使用 JSON、数组和结构体。
完成入门级技能徽章课程“从 BigQuery 数据中挖掘数据洞见”,展示您在以下方面的技能: 编写 SQL 查询、查询公共表、将示例数据加载到 BigQuery 中、 在 BigQuery 中使用查询验证器排查常见的语法错误,以及通过连接到 BigQuery 数据在 Looker Studio 中 创建报告。
Want to turn your marketing data into insights and build dashboards? Bring all of your data into one place for large-scale analysis and model building. Get repeatable, scalable, and valuable insights into your data by learning how to query it and using BigQuery. BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights.
Want to scale your data analysis efforts without managing database hardware? Learn the best practices for querying and getting insights from your data warehouse with this interactive series of BigQuery labs. BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights.
Kubernetes 是最受欢迎的容器编排系统, Google Kubernetes Engine 专为支持 Google Cloud 中的托管式 Kubernetes 部署 而设计。在本高级课程中,您将亲自动手配置 Docker 映像、容器,并部署功能完备的 Kubernetes Engine 应用。 此课程将帮助您掌握在工作流中集成容器编排所需的 实用技能。 想要参加实操实验室挑战赛, 展示您的技能并检验所学知识?完成本课程后,不妨继续参与这项额外的 实验室挑战赛,赢得 Google Cloud 专属数字徽章。 该挑战赛位于在 Google Cloud 上部署 Kubernetes 应用课程的结尾处。
完成设置 Google Cloud 网络课程,赢取技能徽章, 您将了解如何在 Google Cloud Platform 上执行基本的网络组建和管理任务 - 创建自定义网络、添加子网防火墙规则,然后创建虚拟机并测试 虚拟机之间相互通信时的延迟时间。
This fundamental-level quest is unique amongst the other quest offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Professional Cloud Architect Certification. From IAM, to networking, to Kubernetes engine deployment, this quest is composed of specific labs that will put your Google Cloud knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, we recommend that you also review the exam guide and other available preparation resources.
在本入门级课程中,您将了解 Google Cloud 的基础工具和服务。此课程提供了可选视频, 旨在帮助您深入了解和回顾实验中涉及的概念。Google Cloud 基础知识是推荐给 Google Cloud 学员的第一门课程 - 即使您几乎没有云相关知识,也能从中获得实践 经验,并将其直接运用于您的首个 Google Cloud 项目。从编写 Cloud Shell 命令和部署您的第一个虚拟机,到在 Kubernetes Engine 上运行应用 或者使用负载均衡,“Google Cloud 基础知识”都是您了解该平台 基本功能的首选入门级课程。
完成“在 Google Cloud 上设置应用开发环境”课程,赢取技能徽章;通过该课程,您将了解如何使用以下技术的基本功能来构建和连接以存储为中心的云基础设施: Cloud Storage、Identity and Access Management、Cloud Functions 和 Pub/Sub。
完成入门级技能徽章课程为 Compute Engine 实现云负载均衡,展示以下方面的技能: 在 Compute Engine 中创建和部署虚拟机 以及配置网络和应用负载均衡器。